WHAT CLIENTS
HAVE SAID
Feedback and case studies from engineering, product, and marketing teams we've worked with across Malaysia.
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Clients Served
4.8
Average Rating
94%
On-Time Delivery
78%
Return for Second Engagement
CLIENT TESTIMONIALS
Ahmad Iqbal
Engineering Lead, Fintech company, KL
"We'd been meaning to improve our test coverage for two years. Vindara got us from 42% to 71% coverage in eight weeks by targeting the modules where defects had historically clustered. The CI pipeline integration was clean — our team needed less than a day to get comfortable with it. Honestly, it was about what we hoped for, done without unnecessary fuss."
Automated Testing with AI • March 2025
Siti Liyana
Creative Director, Retail Brand, Petaling Jaya
"Our team was producing three to four product image shoots a month. After the Vindara image pipeline, we handle about 60% of routine product imagery in-house. The model learned our aesthetic well — the outputs are consistent with our brand style without constant prompting. It took a few weeks to trust it, but now the team uses it as a natural part of the workflow."
Image Generation Pipeline • February 2025
Rajan Yap
CTO, Logistics SaaS, Shah Alam
"We deployed an internal routing model about eighteen months ago. Since then it's been fine but slightly out of tune — we'd notice performance dips and had no one to properly diagnose them. Vindara's operations retainer changed that. They found two places where the model was degrading quietly and fixed them within the first month. Monthly reports have been useful for our board updates too."
AI Operations Support • January 2025
Nurhana Krishnan
VP Engineering, E-commerce, Kuala Lumpur
"The scoping process was the part I appreciated most. We'd had conversations with two other vendors who both proposed very large engagements. Vindara came in, looked at what we actually needed, and proposed something half the size that addressed the real problem. We ended up running Automated Testing, and the results justified the investment clearly."
Automated Testing with AI • March 2025
Teng Wei
Head of Marketing, Property Developer, KL
"We generate a lot of visualisation assets for property listings — staged interiors, exterior renders, lifestyle shots. The image pipeline has meaningfully reduced how much we're spending on those. I won't say it replaced our design team; it hasn't. But it handles the volume work so they can focus on the pieces that actually need creativity."
Image Generation Pipeline • February 2025
Fariz Azlan
Director of Technology, Insurance, KL
"We're regulated, so data handling was the first thing I asked about. Vindara walked us through their approach before we signed anything — confidentiality agreement, data handling procedures, what happens to our data at end of engagement. That level of care was reassuring. The AI Operations retainer has been running for four months now with no surprises."
AI Operations Support • December 2024
SUCCESS STORIES
Testing Lag in a Rapidly Growing Codebase
A fintech platform had grown to over 200,000 lines of code with a QA team of three. Manual regression coverage had fallen to under 35%, and each release was taking two to three days of manual verification time. Defects in payment-critical code were reaching production at an uncomfortable frequency.
Automated Testing with AI — 8 Weeks
Vindara analysed the defect history and code change patterns to train a risk model. Test case generation was set up for the highest-risk modules first. The system was integrated into the existing GitHub Actions pipeline, and a coverage dashboard was configured for the team lead.
Coverage Up, Release Time Down
Coverage in critical payment modules moved from 38% to 74%. Release verification time dropped from three days to under four hours. The QA team's manual effort shifted toward exploratory testing rather than repetitive regression runs.
+36pp
Coverage gain
87%
Faster releases
Visual Content Volume Straining the Design Team
A Kuala Lumpur property developer was producing 80–100 property listing visuals per month — staging mockups, exterior renders, neighbourhood lifestyle imagery. The design team spent roughly 60% of their time on these routine assets, leaving little capacity for campaign work.
Image Generation Pipeline — 8 Weeks
Vindara selected a base generative model and fine-tuned it on three years of the client's approved property imagery. The model was deployed as an internal web tool accessible to the design team, with prompt guidance documents and defined output categories.
Routine Visual Production Largely Automated
Approximately 65% of routine property listing visuals now originate from the pipeline. The design team's time on routine assets dropped from 60% to under 25%, with the remainder going toward campaign and brand work.
65%
Visuals automated
58%
Team time freed
Deployed AI System With No Dedicated Support
A logistics software company had deployed a route optimisation model eighteen months prior. The original vendor had disengaged, and the internal team lacked ML operations experience. Performance had drifted, and a minor incident had gone unnoticed for eleven days before a client complaint surfaced it.
AI Operations Support — 6-Month Retainer
Vindara onboarded to the existing system, established monitoring, and conducted a performance baseline review. Two areas of model drift were identified and corrected in the first month. A monthly review cadence and incident escalation path were agreed with the client's technology director.
Stable Performance, Faster Issue Detection
Model performance stabilised within six weeks. Over the following five months, three minor issues were detected and resolved within 24 hours each — compared to the eleven-day gap that had previously occurred undetected.
<24h
Issue resolution
0
Client-reported incidents
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